Job Description
We are building the infrastructure for the next era of intelligence. Apex Horizon Technologies is seeking a visionary Lead Generative AI Architect to spearhead our cutting-edge projects. In this role, you will not just implement existing models; you will architect the systems that will power enterprise operations in 2026 and beyond. Join a team of world-class engineers and researchers dedicated to pushing the boundaries of Large Language Models (LLMs), autonomous agents, and ethical AI deployment.
Why Join Us?
- Work on projects that define the future of human-computer interaction.
- Access to state-of-the-art compute resources and proprietary datasets.
- Competitive compensation package and equity options.
- Flexible remote-first culture with a hub in San Francisco.
The Role:
You will be responsible for the end-to-end design and implementation of our Generative AI platform. You will bridge the gap between theoretical research and production-grade engineering, ensuring our solutions are scalable, secure, and transformative.
Responsibilities
- Architectural Design: Design and implement robust, scalable AI architectures utilizing the latest advancements in LLMs, RAG (Retrieval-Augmented Generation), and Agent-based systems.
- Model Optimization: Optimize model inference latency and reduce token costs through quantization, pruning, and deployment on edge devices.
- Team Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Infrastructure Management: Oversee the MLOps pipeline, managing CI/CD, model versioning, and monitoring for production environments.
- Research Integration: Evaluate and integrate emerging research papers and open-source models into production workflows.
- Ethical AI: Ensure all deployed models adhere to strict ethical guidelines and bias mitigation strategies.
Qualifications
- Education: MS or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in software engineering, with at least 3 years specifically focused on Machine Learning and Deep Learning.
- Technical Stack: Proficiency in Python, PyTorch, or TensorFlow. Deep understanding of Transformer architectures.
- Infrastructure: Strong experience with cloud platforms (AWS, GCP, or Azure) and vector databases (Pinecone, Milvus, or Weaviate).
- Problem Solving: Proven track record of solving complex technical challenges and delivering high-impact software products.
- Communication: Excellent verbal and written communication skills, with the ability to translate complex technical concepts for non-technical stakeholders.